Impact of Assimilating Ionosphere and Thermosphere Observations in a Whole Atmosphere Model

Though widely used in the lower atmosphere for both operational and scientific purposes, data assimilation techniques have yet to be extensively adopted in the mesosphere, thermosphere, and ionosphere. This is despite the inherent benefits obtained by combining observations with a background model using data assimilation. To improve representation of variability in the middle and upper atmosphere, as well as provide initial conditions for studying predictability of the near-Earth space weather, the data assimilation capability was developed for the Whole Atmosphere Community Climate Model (WACCM) and WACCM with thermosphere-ionosphere eXtension (WACCMX) using the Data Assimilation Research Testbed (DART) ensemble Kalman filter. A brief overview of the development of WACCM+DART and WACCMX+DART will be provided, including how the application of data assimilation techniques differs between the lower and upper atmospheres. Drawing on several examples, it will be shown that using data assimilation can improve the representation of the chemical, dynamical, and electrodynamics variability of the middle and upper atmospheres. This includes the impact of different types of observations as well as how increasing numbers of observations improves the specification and forecasting of the ionosphere-thermosphere.